AI/ML ENGINEER

Job Title: AI/ML Engineer

Company: Descriptive Solution Private Limited

Location: Okhla Industrial Estate, New Delhi, Delhi

Experience: 1-4 Years

Employment Type: Full-time

Role Summary

We are seeking a skilled AI/ML Engineer to design, train, deploy, and maintain production-ready machine learning models. This role involves working with Natural Language Processing (NLP), data pipelines, and model optimization to ensure our AI services are scalable and integrated into core products.

Key Responsibilities

• Model Development: Design, train, and fine-tune AI/ML models for text, image, or video data, with a focus on NLP.
• ML Pipelines: Develop and manage end-to-end machine learning pipelines, including data collection, cleaning, preprocessing, training, and evaluation.
• Production & Deployment: Deploy models to production environments, manage model serving, monitoring, and versioning.
• Optimization: Enhance model performance, scalability, and reliability for real-world applications.
• Collaboration: Partner with backend and platform teams to integrate AI capabilities into our products.
• MLOps: Ensure comprehensive documentation and adherence to best practices for the model lifecycle and retraining processes.

Required Skills & Experience

• Core AI/ML: Substantial experience with Machine Learning and Deep Learning architectures.
• Frameworks: Proficiency in Python and ML frameworks such as PyTorch or TensorFlow.
• Natural Language Processing: Demonstrated experience with NLP models and associated frameworks.
• Deployment: Hands-on experience with Docker, REST APIs, and cloud/on-premise serving solutions.
• Data Engineering: Expertise in data collection, cleaning, and preparing datasets for ML models.
• Production Grade: Proven track record of building and maintaining production-ready AI systems.

Preferred Qualifications (Nice to Have)

• Experience with large-scale data pipelines and distributed systems.
• Knowledge of MLOps tools and CI/CD practices for machine learning.
• Experience with scalable architectures and microservices.

Technical Stack

Languages: Python

Frameworks: PyTorch, TensorFlow, Keras

Tools: Docker, Git, REST APIs

Domains: NLP, Computer Vision, MLOps